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Variationally Inferred Sampling through a Refined Bound
In this work, a framework to boost the efficiency of Bayesian inference in probabilistic models is introduced by embedding a Markov chain sampler within a variational posterior approximation. We call this framework “refined variational approximation”. Its strengths are its ease of implementation and...
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| 出版年: | Entropy (Basel) |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI
2021
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7832329/ https://ncbi.nlm.nih.gov/pubmed/33477766 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23010123 |
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